Socially adaptive electronic partners for improved support of children’s values: An empirical study with a location-sharing mobile app

Kayal, Alex; Riemsdijk, M. Birna van; Neerincx, Mark A.; Brinkman, Willem‐Paul

doi:10.1016/j.ijcci.2018.09.001

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…To address these tensions adequately, we formulated a general requirement on the creation, activation, and adaptability of agreements (permissions, prohibitions, and obligations to share information, e.g., when the child is staying with a friend; cf. Kayal et al, 2018a , b ).…”

Section: Foundation Of Robotic Lifestyle Partnermentioning

confidence: 98%

“…The Agreement model specifies the underlying concepts with their relations: Type (permission, prohibition, obligation), creditor, debtor, antecedent, consequent, condition, and adaptability (Kayal et al, 2018a , b ; Mioch et al, 2018 ). In the current PAL system, the focus is on the sharing of child's data.…”

Section: Specification Of Situated Human-robot Partnershipsmentioning

confidence: 99%

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Socio-Cognitive Engineering of a Robotic Partner for Child's Diabetes Self-Management

Neerincx

Vught²,

Henkemans³

et al. 2019

Front. Robot. AI

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Social or humanoid robots do hardly show up in "the wild," aiming at pervasive and enduring human benefits such as child health. This paper presents a socio-cognitive engineering (SCE) methodology that guides the ongoing research & development for an evolving, longer-lasting human-robot partnership in practice. The SCE methodology has been applied in a large European project to develop a robotic partner that supports the daily diabetes management processes of children, aged between 7 and 14 years (i.e., Personal Assistant for a healthy Lifestyle, PAL). Four partnership functions were identified and worked out (joint objectives, agreements, experience sharing, and feedback & explanation) together with a common knowledge-base and interaction design for child's prolonged disease self-management. In an iterative refinement process of three cycles, these functions, knowledge base and interactions were built, integrated, tested, refined, and extended so that the PAL robot could more and more act as an effective partner for diabetes management. The SCE methodology helped to integrate into the human-agent/robot system: (a) theories, models, and methods from different scientific disciplines, (b) technologies from different fields, (c) varying diabetes management practices, and (d) last but not least, the diverse individual and context-dependent needs of the patients and caregivers. The resulting robotic partner proved to support the children on the three basic needs of the Self-Determination Theory: autonomy, competence, and relatedness. This paper presents the R&D methodology and the human-robot partnership framework for prolonged "blended" care of children with a chronic disease (children could use it up to 6 months; the robot in the hospitals and diabetes camps, and its avatar at home). It represents a new type of human-agent/robot systems with an evolving collective intelligence. The underlying ontology and design rationale can be used as foundation for further developments of long-duration human-robot partnerships "in the wild."

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Section: Foundation Of Robotic Lifestyle Partnermentioning

confidence: 98%

Section: Specification Of Situated Human-robot Partnershipsmentioning

confidence: 99%

Socio-Cognitive Engineering of a Robotic Partner for Child's Diabetes Self-Management

Neerincx

Vught²,

Henkemans³

et al. 2019

Front. Robot. AI

Self Cite

View full text Add to dashboard Cite

show abstract

“…In our final example we again discuss social robots to show that they do not only provide mere companionship to children and elderly [34], but also can help in maintaining certain types of life style and accompanying medical treatment [19,29,39]. They can help people and particularly children with dealing with several kinds of diseases such as autism [21,42,55] and diabetes [11,12].…”

Section: Behavior Change Managementmentioning

confidence: 99%